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How can character count toward identifying good credit clients?

The financing gap for micro, small and medium-sized enterprises (MSMEs) in Latin America and the Caribbean was estimated at $1.2 trillion in 2017, nearly a quarter of the global emerging market total. If this gap were a country, not only would it be a credit desert for most inhabitants, but it would edge out Mexico as number 15 on the list of the world’s largest economies in terms of nominal gross domestic product (GDP).

How can character count toward identifying good credit clients?

At a macro level, this gap is mainly due to weaknesses and bottlenecks in the region’s financial infrastructure, which includes a constellation of institutions, technologies, regulations, and standards that enable effective financial intermediation, such as efficient payment systems, reliable credit bureaus, unified collateral registries, and judicial systems that enforce legal contracts. At a transaction level, this means that it is hard for banks to assess the credit risk of MSMEs that are often run by sole proprietors without credit histories, audited financial statements, or assets to use as guarantees. And so, the gap widens.

A new way to evaluate creditworthiness

Fintech companies can help banks and governments in the region leapfrog these bottlenecks by providing essential services and information in a new way. For example, instead of relying on dispersed public notaries for collateral registry, governments could look to blockchain to create secure, centralized, and readily accessible records on security interests. Similarly, instead of only depending on credit bureaus, financial institutions can take advantage of the wealth of data that fintech solutions can capture on psychometrics, digital payments, mobile phone usage, or social networks to help evaluate the creditworthiness of potential borrowers.

IDB Invest and the Multilateral Investment Fund (MIF) had the opportunity to pilot one of these solutions in Peru. Together with the Entrepreneurial Finance Lab (EFL), prior to its merger with Lenddo in 2017, we tested EFL’s psychometric credit scoring tool for the first time in Latin America on a commercial basis with a large bank looking to expand its MSME portfolio. As part of this pilot, IDB Invest provided a risk sharing guarantee to the bank to cover a portion of its new credit exposure.

Taking a cue from long-standing employer hiring practices, this tool assesses what is hiding in plain sight: people’s personalities and character — namely conscientiousness, honesty, and general intelligence — as key predictors of potential borrowers’ ability and willingness to repay loans.

Entrepreneurs without credit histories are good clients

Results from this pilot experience show that character counts when identifying good credit clients. This was particularly evident among loan applicants without a credit history — meaning entrepreneurs with “thin” credit bureau files who had either never received credit from a formal financial institution or had not done so recently — who gained access to financing without affecting the risk of the bank’s portfolio. This indicates that these previously overlooked clients are indeed repaying their debt. More specifically, applicants without credit histories who were approved by the EFL tool were four times more likely to access loans within six months from any financial institution versus those who did not pass the EFL screening (72% versus 18%, respectively).

Given the unmet need for access to capital among MSMEs in the region — and the untapped business opportunity they represent for lenders — psychometric credit scoring tools offer a practical solution for both banks and potential borrowers, particularly in countries where well-developed credit bureaus are in the process of consolidation.

And, as financial institutions seek to innovate in the face of mounting digital disruption and are increasingly looking for new ways to broaden their client base, tools such as these can help them paint a more complete creditworthiness profile of potential borrowers and mitigate the risk of MSME lending, while helping the region to fill the trillion-dollar gap.

For more information, see Are Psychometric Tools a Viable Screening Method for Small and Medium Enterprise Lending? Evidence from Peru, part of IDB Invest’s Development through the Private Sector Series, or a brief summarizing this study here.

A story of psychometric tools


Irani Arraiz

Irani Arráiz es economista en la División de Efectividad en el Desarrollo de BID Invest. Sus áreas de experticia incluyen evaluación de políticas y

Development Impact

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